Background: Rising nosocomial infections pose high risks, especially for immunocompromised leukemia patients, necessitating targeted research to enhance patient care and outcomes.The objective of this study was to investigate the impact of nosocomial infections (CDI) on patients hospitalized with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML).
Methods: Our study was a retrospective analysis of adult patients hospitalized with a primary diagnosis of ALL or AML, using the Nationwide Inpatient Sample (NIS) database for 2020. Primary outcomes included the incidence of nosocomial CDI and all-cause inpatient mortality. Secondary outcomes included hospital length of stay, resource utilization, and morbidity. Statistical analyses were conducted with STATA (address). Fisher's exact test was utilized to compare proportions, while the Student's t test was employed for continuous variables. Multivariate logistic and linear regression analyses were used to adjust for confounding variables.
Results: We found in 21 135 ALL and 58 560 AML adult patients that the CDI incidences were 2.77% and 3.0%, respectively. ALL and AML patients with CDI had adjusted mortality odds ratios of 3.02 ( = .003) and 1.51 ( = .02). Hospital length of stay was extended by mean differences of 10.16 days (ALL) and 8.33 days (AML) for those with CDI compared to those without it. In addition, patients with CDI displayed a significantly higher incidence of acute kidney injury, sepsis, vasopressor use, and intensive care unit admissions.
Conclusion: This study highlights the significant impact of CDI infections on health outcomes for leukemia patients, emphasizing the need for robust infection control measures, early detection, and aggressive management of CDI to improve patient outcomes and minimize healthcare costs.
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http://dx.doi.org/10.36518/2689-0216.1748 | DOI Listing |
Recent Pat Anticancer Drug Discov
January 2025
Department of Hematology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, 510282, P.R. China.
Background: BCL-2 was the first gene identified to have antiapoptotic effects, and venetoclax is an oral selective BCL-2 inhibitor, which has great potential in the treatment of patients with acute myeloid leukemia (AML) who are not candidates for intensive therapy. Notably, posaconazole, an oral antifungal drug, is also a strong factor that can affect blood venetoclax concentrations. To the best of our knowledge, the relationship between BCL-2 expression, posaconazole, and venetoclax, as well as their influence on treatment efficacy and the prognosis of patients with AML, has not been reported.
View Article and Find Full Text PDFCommun Stat Theory Methods
March 2024
Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, 53226, Wisconsin,USA.
Competing risks data in clinical trial or observational studies often suffer from cluster effects such as center effects and matched pairs design. The proportional subdistribution hazards (PSH) model is one of the most widely used methods for competing risks data analyses. However, the current literature on the PSH model for clustered competing risks data is limited to covariate-independent censoring and the unstratified model.
View Article and Find Full Text PDFEur J Case Rep Intern Med
December 2024
Intensive Care Unit, Pedro Hispano Hospital, Matosinhos Local Health Unit, Matosinhos, Portugal.
Background: Hemophagocytic lymphohistiocytosis (HLH) is a rare, life-threatening hyperinflammatory syndrome marked by excessive immune activation. It can be triggered by various factors, including infections, malignancies, and autoimmune diseases, making the diagnosis challenging due to its overlap with other severe conditions.
Case Reports: We discuss two intensive care unit (ICU) cases illustrating the diverse manifestations of HLH and the critical importance of early recognition and treatment.
Commun Stat Simul Comput
August 2023
Division of Biostatistics, Medical College of Wisconsin, Milwaukee, WI 53226, USA.
Observational studies with right-censored data often have clustered data due to matched pairs or a study center effect. In such data, there may be an imbalance in patient characteristics between treatment groups, where Kaplan-Meier curves or unadjusted cumulative incidence curves can be misleading and may not represent the average patient on a given treatment arm. Adjusted curves are desirable to appropriately display survival or cumulative incidence curves in this case.
View Article and Find Full Text PDFBackground: Rising nosocomial infections pose high risks, especially for immunocompromised leukemia patients, necessitating targeted research to enhance patient care and outcomes.The objective of this study was to investigate the impact of nosocomial infections (CDI) on patients hospitalized with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML).
Methods: Our study was a retrospective analysis of adult patients hospitalized with a primary diagnosis of ALL or AML, using the Nationwide Inpatient Sample (NIS) database for 2020.
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